An increase or decrease in the size of digital images is often required. Increasing the size of a picture is required when, for example, it is desirable to obtain large prints. The quality of the scaling method then directly defines the quality of printed materials. Further, displaying a picture comprising a high number of pixels (12 megapixels for example) on a screen with limited features (a display of 2 megapixels for example, 6 times less) also requires better methods to reduce the size of a given picture by trying to keep the initial picture accuracy.
Today an image size can be changed in several ways. Considering the objective of doubling the size of a given image (dimensions or surface), the state of the art proposes several approaches. The easiest way of doubling an image's size is nearest-neighbor interpolation, where every pixel is replaced with four pixels of the same color. The resulting image is larger than the original, and preserves all the original detail, but has undesirable jaggedness. The diagonal lines, for example, may show the characteristic “stairway” shape (aliasing). Other scaling methods are better at preserving smooth contours in the image. For example, bilinear interpolation produces the better results. Linear (or bilinear, in two dimensions) interpolation is typically better than the nearest-neighbor system for changing the size of an image, but causes some undesirable softening of details and can still be somewhat jagged. Better scaling methods today include bicubic interpolation. This kind of method leverages block prediction and this implies drawbacks. With a large resizing for example, the image appears to be blurred.
Another method is to use fractal analysis of the image, but it requires huge computing resources. In conclusion, current methods do not allow to increase more than a factor two a given picture size without visible defaults or artifacts.
U.S. Pat. No. 7,146,055 entitled “Image processing decompression apparatus and method of using same different scaling algorithms simultaneously” discloses a data decompression apparatus, comprising: a decompression unit for providing separated full resolution luminance and chrominance color space components indicative of individual image pixels in a compressed color space data stream; a plurality of image processing units for applying a scaling process to the full resolution luminance color space components and for applying another scaling process to the individual ones of the chrominance color space components to provide decompressed full resolution luminance and chrominance color space data to facilitate image zoom operations. This approach is not sufficient.
In order to address these and other problems, there is a need for an enhanced method of resizing an image.